A scoping review identifies comments suggesting modifications to PRISMA-P 2015
Bibliographic record
Abstract
OBJECTIVES: To identify, summarize, and analyze published comments relevant to the PRISMA-P (Preferred Reporting Items for Systematic reviews and Meta-Analyses Protocols) 2015 reporting guideline for systematic review protocols, with special emphasis on suggestions for guideline modifications. METHODS: We included documents (eg, empirical studies and social media posts) that included comments relevant to PRISMA-P 2015. We searched bibliographic databases (eg, Embase, MEDLINE, Scopus, from January 1st 2015 to February 2nd 2024) and other sources (eg, BMJ rapid responses, BMC Blog Network, from January 1st 2015 to April 22nd 2024). Two authors independently assessed documents for inclusion, extracted data, and categorized comments. We categorized comments as "suggestion for modification to the wording of an existing PRISMA-P 2015 item," "suggestion for a new item," "suggestion for deletion of an existing PRISMA-P 2015 item," or "additional comment." We categorized each comment into themes and provided a summary and examples of the proposed suggestions. We analyzed the characteristics of the suggestions by describing the rationale and comparing with existing PRISMA-P 2015 guidance. RESULTS: We assessed full text of 1912 potentially eligible documents and included 28 documents with 38 comments. 11 comments suggested modifications to existing guideline items. Multiple comments proposed modifications to items related to eligibility criteria (three comments made different suggestions, for example, one comment suggested to include reporting guidance relating to retracted papers) and data synthesis (three comments made different suggestions, eg, one comment suggested to add reporting guidance relating to prediction intervals for random-effects meta-analyses). There were 11 comments suggesting new items. The data items section of PRISMA-P 2015 received the most comments (five comments made different suggestions, eg, three comments suggested to add content on prespecifying whether authors plan to extract information on funding and conflicts of interest among the included studies). None of the included comments suggested deleting items or content. Most of the suggestions provided a rationale directly in the document, and around two-thirds of the suggestions referred to content in addition to PRISMA-P 2015 or asked for more extensive guidance than what is included. CONCLUSION: The issues raised provide context to authors, peer reviewers, editors, and readers of systematic review protocols using PRISMA-P 2015 and inform the planned update of the guideline.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.526 | 0.854 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.006 | 0.014 |
| Bibliometrics | 0.026 | 0.021 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.011 | 0.019 |
| Research integrity | 0.022 | 0.017 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".